RE: st: svyset for survey with oversampling

Guilherme,
I should have also referred you to some literature:
Stapleton, L.M. (2008). Analysis of data from complex surveys. In E.D. De Leeuw, J.J. Hox, & D.A. Dillman (Eds.), International Handbook of Survey Methodology (pp. 342-369). Clifton, NJ: Psychology Press.
Lee, E.S., & Forthofer, R.N. (2005). Analyzing complex survey data. (2nd ed.). Thousand Oaks, CA: Sage.
Binder, D.A., Roberts, G.R. (2003). Design-based and model-based methods for estimating model parameters. In R.L. Chambers & C. Skinner (eds.), Analysis of Survey Data (pp. 29-48). Chichester: Wiley.
Again, it's certainly possible to use those adjusted weights together with some method for correcting the standard errors for stratification and clustering (e.g., replication methods, Taylor linearization). Hope this helps,
Cam
----------------------------------------
> From: chihayakenji1893@gmail.com
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: svyset for survey with oversampling
> Date: Sat, 22 Aug 2009 02:22:34 +0900
>
> Hi Cam,
>
> Thank you for your reply. They do provide a weight variable to use
> when analysing the samples together to correct for urban population
> oversampling, but I believe that it is not taking in to account the
> other biases introduced by the multistage sampling.
>
> It would be nice if there was a solution that allowed me both to
> correct the biases of multistage sampling and of oversampling of the
> urban population.
>
>
> Guilherme
>
> On 2009/08/22, at 2:12, Cameron McIntosh wrote:
>
>> Hi Guilherme,
>> They don't provide some adjustment to the sampling weights to allow
>> for combined analysis?
>> Cam
>>
>> ----------------------------------------
>>> From: chihayakenji1893@gmail.com
>>> To: statalist@hsphsun2.harvard.edu
>>> Subject: st: svyset for survey with oversampling
>>> Date: Sat, 22 Aug 2009 02:00:35 +0900
>>>
>>> Dear Statalist Members
>>>
>>> It is my first post to this list. My name is Guilherme Kenji Chihaya
>>> and I am currently a graduate student in Tohoku University, Japan. I
>>> am using a data set called Life Histories and Social Change in
>>> Contemporary China. It is a survey in which the rural and urban
>>> populations of China were treated as different populations and each
>>> one was sampled for about 4000 samples using multistage sampling with
>>> clustering.
>>>
>>> The proportion of China's rural population was about 70% by the time
>>> of the survey, however, this survey is designed so that it accounts
>>> for 50% of the whole sample if you try to analyse the two samples
>>> together. Besides this problem, it still has all the other biases
>>> caused by multistage clustering.
>>>
>>> I wonder if it is possible to use svyset to correct all these biases
>>> so that I can analyse the two samples as one single dataset. The
>>> codebook for the survey is incomplete, it states that the data is
>>> supposed to be analysed using Stata complex samples functionality but
>>> the part about how to use it is unfinished in the available version.
>>> There are variables identifying the primary sample unit and the
>>> stratum used for sampling. However, I don't know how to deal with the
>>> rural-urban disproportionality.
>>>
>>> I would appreciate if someone could help me with this, especially if
>>> there is anybody in this list that is familiar with this dataset.
>>>
>>> Guilherme Kenji Chihaya
>>>
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